Snow avalanche impact pressure - vulnerability relations for use in risk assessment
Bibliographic record
Abstract
Use of formal risk analysis to assess avalanche danger is currently limited by a lack of knowledge of how avalanche impact pressures damage structures and cause fatalities. That is, the vulnerability component of risk is poorly specified. In this paper we outline a method for deriving vulnerability values as a function of position downslope for a range of avalanche sizes. The method is based on the weighted average of vulnerability and uses an avalanche-dynamics model embedded within a statistical framework. The models seem to behave in a consistent manner. By allowing avalanche size and stopping position to vary and calculating vulnerability as a function of distance from the stopping position, vulnerability values are less approximate than the assumption of a constant vulnerability value for each individual size. When the assumptions underlying the impact pressure - vulnerability relation are perturbed, the results seem to be robust. The method outlined here should provide a way for avalanche experts to reformulate danger zones based on return period and impact pressure so that they are set within a risk framework.Key words: risk, vulnerability, snow, avalanches, impact pressure.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".